# Wang sees data and know-how as China’s AI advantages

Markdown copy of https://realalpha.app/s/wang-sees-data-and-know-how-as-chinas-ai-advantages/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Alexandr Wang](https://realalpha.app/builders/alexandr-wang/) · Alexandr Wang is CEO of Scale AI. · Dropped out of MIT to co-found Scale AI in 2016; Meta invested $14.3B in it in 2025 and hired him to lead Superintelligence Labs.
- Host: [Garry Tan](https://realalpha.app/people/garry-tan/) · President & CEO, Y Combinator · Co-founded Posterous and Initialized Capital, an early Coinbase backer.
- Host: [Harj Taggar](https://realalpha.app/people/harj-taggar/) · Managing partner, Y Combinator · Co-founded Auctomatic with the Collison brothers and later Triplebyte.
- Host: [Diana Hu](https://realalpha.app/people/diana-hu/) · Managing partner, Y Combinator · CTO of Escher Reality; after Niantic bought it, ran AR for Pokémon GO.
- Host: [Jared Friedman](https://realalpha.app/people/jared-friedman/) · Managing partner, Y Combinator · Co-founded Scribd, which YC funded in 2006; has advised 20+ YC unicorns.
- Show: Lightcone
- Episode: [Alexandr Wang: Building Scale AI, Transforming Work With Agents & Competing With China](https://realalpha.app/v/5noIKN8t69U/), Jun 18, 2025
- Moment: 47:58 to 52:08 of the episode (4 min), playing on https://realalpha.app/s/wang-sees-data-and-know-how-as-chinas-ai-advantages/; the episode from there: https://realalpha.app/v/5noIKN8t69U/?t=2878

## Quote

> “The simplest explanation for me about why the Chinese models are so good **is espionage**.”
> — [Alexandr Wang](https://realalpha.app/builders/alexandr-wang/) at [48:07](https://realalpha.app/v/5noIKN8t69U/?t=2887) · Lightcone

## Takeaways

1. He attributes some Chinese progress to leaked training know-how.
2. China has government-backed data-labeling programs.
3. Wang sees a U.S. edge, but says China could catch up.

## About this segment

Alexandr Wang argues that training know-how can leak from frontier labs and says China is well positioned on data, including through government-backed labeling programs. He sees the U.S. as advantaged overall, but not assured of staying ahead.

From “Alexandr Wang: Building Scale AI, Transforming Work With Agents & Competing With China”, Jun 18, 2025. [Watch the full episode](https://realalpha.app/v/5noIKN8t69U/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[48:03](https://realalpha.app/v/5noIKN8t69U/?t=2883) What do you think we can do to just make sure that it's the American models that are ahead? Or, you know, is that written in the stars? Or, you know, something tells me that's not. The simplest explanation for me about why the Chinese models are so good is espionage. I think that there's a lot of secrets in how these frontier models are trained. And when I say secrets, it sounds more interesting than they are, but there's just a lot of tacit knowledge.

[48:28](https://realalpha.app/v/5noIKN8t69U/?t=2908) There's a lot of like, you know, tricks and small and intuitions about where to set the hyper parameters and like, you know, ways to make these models work and to get the model training to work. The Chinese labs have been have been able to move so quickly and accelerate and make such fast progress, whereas some even like very talented U.S. labs like have made progress less quickly. And I just purely think it's because, you know, a lot of the secrets about how to train these models, you know, the secrets leave the frontier labs and make their way back to these Chinese labs.

[49:01](https://realalpha.app/v/5noIKN8t69U/?t=2941) I think the only way to model the future is that China has pretty advanced models. You know, the solace right now is they're not the best models. They're sort of like a half step behind, let's say. But it's tough to model what will happen when it's sort of truly neck and neck. we're very behind on energy production which is just pure regulation like that could be fixed in two seconds but you know hasn't been yet that's a huge problem i mean if you look at you know not that the past will be a predictor of the future if you look at what u.s total grid production looks like it's like looks flat as a pig and if you look at um you know chinese i saw that uh aggregate uh you know grid production it's like you know it's doubled over the past decade it's just like it's just this like straight up i saw that and it's astonishing it's i mean that's just a policy

[49:49](https://realalpha.app/v/5noIKN8t69U/?t=2989) failure china just you know the vast majority of that is coal and coal's growing in china and um in the united states uh actually renewables have grown a lot but renewables trade off against the uh the sort of fossil fuels so we've sort of like done a done a transition of our of our um energy grid whereas they're just continuing to compound let's say we have this issue on power production but we're advantaged in chips i think like net net we will come out ahead on compute um if you look at data i mean this goes towards a lot of the questions you've been you've been asking about but like i mean i think china is like fundamentally very well positioned on data um it's weird to say because it's obviously like you know we help all the american companies with data in china they can ignore copyright or other privacy rules and and they can sort of um you

[50:37](https://realalpha.app/v/5noIKN8t69U/?t=3037) know build these large models without abandon and then and then the second issue is that um There's actually large scale government programs in China for data labeling. There are, you know, seven data labeling centers, like in various cities that have been started up by the government itself. There's large scale subsidies for AI companies to use data labeling, a voucher system. In fact, there's like college programs because, you know, one of the interesting things is in China, like employment is such a large national priority that they like, you know, when they have a strategic area like ai they'll like figure out okay what are all the jobs and they'll like create these like funnels to um to to create those jobs and then we're seeing this in robotics data too where like there's already in china they're like large-scale factories full of

[51:23](https://realalpha.app/v/5noIKN8t69U/?t=3083) robots that just go and collect data um and uh and strangely enough like even a lot of u.s companies today actually rely on data from china in training these like robotics foundation models long story short i think china likely has a data an advantage on data and then the algorithms um you know the us is on net much more innovative but if espionage continues to be a reality then like you know you're basically even on algorithms so um so it's hard to model but i think that probably like you know it's like 60 40 70 30 that the united states like has like in undeniable I will continue to advantage, but there's like a lot of worlds where China just like catches up or potentially even overtakes.